{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "GEN_8_StyleGAN2.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/cxbxmxcx/GenReality/blob/master/GEN_8_StyleGAN2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rS1wUgN15uyB"
      },
      "source": [
        "#@title IMPORTS\r\n",
        "import os\r\n",
        "import sys\r\n",
        "import time\r\n",
        "import datetime"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dpf_MyiJzc6l",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5e9ebf5a-a2c3-42ca-f61a-7c9cf996124d"
      },
      "source": [
        "from google.colab import drive\r\n",
        "\r\n",
        "drive.mount('/content/gdrive')\r\n",
        "os.makedirs('/content/gdrive/MyDrive/stylegan2', exist_ok=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RXeA0GTK0dhv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "aefe57f3-ebab-49cb-fab9-705c9855dd52"
      },
      "source": [
        "cd /content/gdrive/MyDrive/stylegan2"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/gdrive/MyDrive/stylegan2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z65V95AFk1Y_"
      },
      "source": [
        "#@title INSTALLS\r\n",
        "!pip install stylegan2_pytorch --quiet"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rVBTY_4wwfbq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5da1513c-a9ff-493a-8085-946871c5af30"
      },
      "source": [
        "#@title HYPERPARAMETERS \n",
        "dataset_name = \"foods\" #@param [\"img_align_celeba\",\"foods\",\"cars_all\"]\n",
        "\n",
        "\n",
        "datasets = { \"img_align_celeba\" : { \"url\" : 'https://www.dropbox.com/s/5hznryk2m0qxs2m/img_align_celeba.zip?dl=1'},\n",
        "             \"foods\" : { \"url\" : \"https://www.dropbox.com/s/scmccjzoa0i5arx/foods.zip?dl=1\"},\n",
        "             \"cars_all\" : { \"url\" : \"https://www.dropbox.com/s/2zyep29yp4ke7fi/cars_all.zip?dl=1\"}\n",
        "            }\n",
        "\n",
        "img_root_folder = 'images3'\n",
        "os.makedirs(img_root_folder, exist_ok=True)\n",
        "image_folder = img_root_folder + \"/%s\" % dataset_name \n",
        "print(f\"Image data folders constructed {image_folder}\")\n",
        "os.makedirs(image_folder, exist_ok=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Image data folders constructed images3/foods\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jzze0ldCx1O_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "09eb9029-5443-4664-fe7d-3a7c37815231"
      },
      "source": [
        "#@title DOWNLOAD IMAGES\n",
        "if len(os.listdir(image_folder)) == 0:\n",
        "    from io import BytesIO\n",
        "    from urllib.request import urlopen\n",
        "    from zipfile import ZipFile\n",
        "    zipurl = datasets[dataset_name]['url']\n",
        "    with urlopen(zipurl) as zipresp:\n",
        "        with ZipFile(BytesIO(zipresp.read())) as zfile:        \n",
        "            zfile.extractall(img_root_folder)\n",
        "            print(f\"Downloaded & Extracted {zipurl}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloaded & Extracted https://www.dropbox.com/s/scmccjzoa0i5arx/foods.zip?dl=1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VSQA0h0L64fr",
        "outputId": "083c6e2e-7184-4d2d-f225-7a65b2858357"
      },
      "source": [
        "!stylegan2_pytorch --data $image_folder --name $dataset_name"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "continuing from previous epoch - 88\n",
            "loading from version 1.5.14\n",
            "foods<images3/foods>:  59% 88000/150000 [00:00<?, ?it/s]G: -0.33 | D: 0.97 | GP: 0.09 | PL: 0.91\n",
            "foods<images3/foods>:  59% 88044/150000 [00:57<24:49:54,  1.44s/it]G: 0.56 | D: 0.87 | GP: 0.53 | PL: 0.91\n",
            "foods<images3/foods>:  59% 88097/150000 [02:02<22:05:07,  1.28s/it]G: 0.73 | D: 0.63 | GP: 0.14 | PL: 0.91\n",
            "foods<images3/foods>:  59% 88143/150000 [02:57<20:42:39,  1.21s/it]G: 0.81 | D: 1.05 | GP: 0.58 | PL: 0.91\n",
            "foods<images3/foods>:  59% 88191/150000 [03:54<20:09:01,  1.17s/it]G: 1.44 | D: 0.62 | GP: 0.14 | PL: 0.92\n",
            "foods<images3/foods>:  59% 88248/150000 [05:02<19:47:35,  1.15s/it]G: 0.91 | D: 0.86 | GP: 1.14 | PL: 0.92\n",
            "foods<images3/foods>:  59% 88296/150000 [06:00<20:40:38,  1.21s/it]G: 1.20 | D: 0.85 | GP: 0.03 | PL: 0.92\n",
            "foods<images3/foods>:  59% 88344/150000 [06:57<19:53:57,  1.16s/it]G: 0.49 | D: 1.10 | GP: 0.25 | PL: 0.92\n",
            "foods<images3/foods>:  59% 88391/150000 [07:54<20:23:03,  1.19s/it]G: -0.08 | D: 0.92 | GP: 0.84 | PL: 0.92\n",
            "foods<images3/foods>:  59% 88449/150000 [09:04<20:57:51,  1.23s/it]G: -0.03 | D: 0.71 | GP: 0.15 | PL: 0.92\n",
            "foods<images3/foods>:  59% 88496/150000 [09:59<20:06:34,  1.18s/it]G: 1.13 | D: 0.86 | GP: 0.02 | PL: 0.92\n",
            "foods<images3/foods>:  59% 88549/150000 [11:05<21:22:10,  1.25s/it]G: 1.07 | D: 0.88 | GP: 0.32 | PL: 0.93\n",
            "foods<images3/foods>:  59% 88596/150000 [11:59<19:52:04,  1.16s/it]G: 0.95 | D: 0.87 | GP: 1.02 | PL: 0.93\n",
            "foods<images3/foods>:  59% 88641/150000 [12:56<21:11:51,  1.24s/it]G: -1.15 | D: 1.44 | GP: 0.25 | PL: 0.94\n",
            "foods<images3/foods>:  59% 88700/150000 [14:05<19:47:25,  1.16s/it]G: 0.43 | D: 0.76 | GP: 1.42 | PL: 0.94\n",
            "foods<images3/foods>:  59% 88747/150000 [15:02<20:13:33,  1.19s/it]G: 0.52 | D: 0.88 | GP: 0.07 | PL: 0.94\n",
            "foods<images3/foods>:  59% 88797/150000 [16:02<20:22:43,  1.20s/it]G: 1.02 | D: 0.74 | GP: 0.15 | PL: 0.94\n",
            "foods<images3/foods>:  59% 88843/150000 [16:56<19:58:10,  1.18s/it]G: 0.46 | D: 1.52 | GP: 0.07 | PL: 0.94\n",
            "foods<images3/foods>:  59% 88891/150000 [17:53<19:39:03,  1.16s/it]G: 1.84 | D: 0.77 | GP: 1.20 | PL: 0.95\n",
            "foods<images3/foods>:  59% 88948/150000 [19:00<19:31:52,  1.15s/it]G: 1.16 | D: 0.89 | GP: 0.13 | PL: 0.95\n",
            "foods<images3/foods>:  59% 88997/150000 [20:00<20:44:33,  1.22s/it]G: 0.81 | D: 0.92 | GP: 0.36 | PL: 0.95\n",
            "foods<images3/foods>:  59% 89041/150000 [20:56<21:13:23,  1.25s/it]G: -0.48 | D: 1.16 | GP: 0.16 | PL: 0.95\n",
            "foods<images3/foods>:  59% 89098/150000 [22:04<20:20:39,  1.20s/it]G: 1.11 | D: 0.93 | GP: 0.07 | PL: 0.95\n",
            "foods<images3/foods>:  59% 89145/150000 [23:00<20:37:41,  1.22s/it]G: 1.02 | D: 0.76 | GP: 0.04 | PL: 0.95\n",
            "foods<images3/foods>:  59% 89200/150000 [24:05<19:50:54,  1.18s/it]G: 0.46 | D: 1.09 | GP: 0.04 | PL: 0.95\n",
            "foods<images3/foods>:  59% 89244/150000 [24:58<19:38:58,  1.16s/it]G: 1.07 | D: 0.47 | GP: 0.35 | PL: 0.95\n",
            "foods<images3/foods>:  60% 89298/150000 [26:05<20:44:09,  1.23s/it]G: 0.16 | D: 0.97 | GP: 0.26 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89343/150000 [27:10<20:06:19,  1.19s/it]G: 0.56 | D: 1.09 | GP: 0.35 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89395/150000 [28:03<19:57:44,  1.19s/it]G: 0.47 | D: 0.61 | GP: 0.10 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89441/150000 [28:59<20:38:11,  1.23s/it]G: 0.76 | D: 0.69 | GP: 0.75 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89491/150000 [29:57<19:38:33,  1.17s/it]G: 0.84 | D: 1.08 | GP: 0.40 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89546/150000 [31:03<20:10:44,  1.20s/it]G: -0.85 | D: 1.26 | GP: 0.62 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89594/150000 [32:00<20:02:27,  1.19s/it]G: 1.16 | D: 0.90 | GP: 0.36 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89641/150000 [32:57<20:26:48,  1.22s/it]G: 0.27 | D: 0.89 | GP: 0.07 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89698/150000 [34:04<20:08:52,  1.20s/it]G: 0.23 | D: 0.82 | GP: 0.24 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89747/150000 [35:01<19:38:30,  1.17s/it]G: 1.36 | D: 1.31 | GP: 0.11 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89794/150000 [35:58<20:00:29,  1.20s/it]G: 0.63 | D: 0.97 | GP: 0.87 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89843/150000 [36:55<19:27:17,  1.16s/it]G: 0.09 | D: 0.98 | GP: 0.58 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89900/150000 [38:02<19:10:51,  1.15s/it]G: 1.11 | D: 1.12 | GP: 0.18 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89949/150000 [39:01<20:08:06,  1.21s/it]G: 2.19 | D: 0.87 | GP: 0.39 | PL: 0.96\n",
            "foods<images3/foods>:  60% 89996/150000 [39:55<19:09:41,  1.15s/it]G: 0.93 | D: 0.99 | GP: 0.34 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90046/150000 [40:57<20:05:20,  1.21s/it]G: 1.01 | D: 0.88 | GP: 0.42 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90095/150000 [41:55<19:29:54,  1.17s/it]G: 0.65 | D: 0.78 | GP: 0.11 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90143/150000 [42:52<19:19:28,  1.16s/it]G: 0.84 | D: 0.94 | GP: 1.53 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90192/150000 [43:51<19:09:15,  1.15s/it]G: 0.83 | D: 0.77 | GP: 0.14 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90249/150000 [45:00<20:14:25,  1.22s/it]G: 0.38 | D: 1.05 | GP: 0.58 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90298/150000 [45:57<19:34:13,  1.18s/it]G: 0.57 | D: 0.94 | GP: 0.26 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90346/150000 [46:55<20:02:32,  1.21s/it]G: 0.04 | D: 0.97 | GP: 0.16 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90393/150000 [47:50<19:58:48,  1.21s/it]G: 1.52 | D: 0.76 | GP: 0.29 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90449/150000 [48:57<19:59:00,  1.21s/it]G: 0.56 | D: 0.90 | GP: 0.29 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90498/150000 [49:55<19:42:59,  1.19s/it]G: 0.68 | D: 0.72 | GP: 0.12 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90547/150000 [50:51<19:20:47,  1.17s/it]G: 1.00 | D: 1.02 | GP: 0.12 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90595/150000 [51:49<19:47:13,  1.20s/it]G: 1.91 | D: 0.75 | GP: 0.37 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90645/150000 [52:48<19:42:14,  1.20s/it]G: 0.49 | D: 0.91 | GP: 0.67 | PL: 0.96\n",
            "foods<images3/foods>:  60% 90693/150000 [53:46<20:11:58,  1.23s/it]G: 1.41 | D: 0.97 | GP: 0.32 | PL: 0.97\n",
            "foods<images3/foods>:  60% 90742/150000 [54:43<19:28:56,  1.18s/it]G: 0.83 | D: 0.74 | GP: 0.07 | PL: 0.96\n",
            "foods<images3/foods>:  61% 90799/150000 [55:50<19:14:27,  1.17s/it]G: 0.87 | D: 0.75 | GP: 0.13 | PL: 0.97\n",
            "foods<images3/foods>:  61% 90848/150000 [56:47<18:50:42,  1.15s/it]G: 1.54 | D: 0.63 | GP: 0.06 | PL: 0.97\n",
            "foods<images3/foods>:  61% 90895/150000 [57:44<19:18:57,  1.18s/it]G: 0.81 | D: 0.71 | GP: 0.40 | PL: 0.98\n",
            "foods<images3/foods>:  61% 90943/150000 [58:40<18:51:45,  1.15s/it]G: 0.62 | D: 1.25 | GP: 0.52 | PL: 0.98\n",
            "foods<images3/foods>:  61% 90991/150000 [59:50<19:11:06,  1.17s/it]G: 1.31 | D: 0.96 | GP: 0.49 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91049/150000 [1:00:50<20:02:01,  1.22s/it]G: 0.38 | D: 0.74 | GP: 0.20 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91098/150000 [1:01:47<19:24:46,  1.19s/it]G: 0.49 | D: 1.25 | GP: 1.54 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91145/150000 [1:02:44<19:55:32,  1.22s/it]G: 1.18 | D: 0.75 | GP: 0.01 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91193/150000 [1:03:40<19:40:57,  1.20s/it]G: 0.43 | D: 1.06 | GP: 1.06 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91241/150000 [1:04:37<19:52:24,  1.22s/it]G: 0.27 | D: 0.75 | GP: 0.68 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91297/150000 [1:05:44<19:57:36,  1.22s/it]G: 0.61 | D: 0.91 | GP: 0.20 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91347/150000 [1:06:42<19:09:47,  1.18s/it]G: 0.43 | D: 0.77 | GP: 0.62 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91394/150000 [1:07:39<19:57:28,  1.23s/it]G: 0.69 | D: 0.76 | GP: 0.22 | PL: 0.99\n",
            "foods<images3/foods>:  61% 91444/150000 [1:08:37<18:57:46,  1.17s/it]G: 3.61 | D: 1.21 | GP: 0.89 | PL: 0.99\n",
            "foods<images3/foods>:  61% 91499/150000 [1:09:43<19:20:14,  1.19s/it]G: 1.27 | D: 0.98 | GP: 0.04 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91547/150000 [1:10:40<19:02:19,  1.17s/it]G: 0.35 | D: 0.92 | GP: 0.40 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91594/150000 [1:11:37<19:43:48,  1.22s/it]G: 0.78 | D: 0.95 | GP: 0.65 | PL: 0.99\n",
            "foods<images3/foods>:  61% 91650/150000 [1:12:45<19:53:16,  1.23s/it]G: 1.99 | D: 0.87 | GP: 0.06 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91699/150000 [1:13:42<19:16:09,  1.19s/it]G: 0.22 | D: 1.34 | GP: 1.07 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91745/150000 [1:14:38<19:46:37,  1.22s/it]G: 0.49 | D: 0.93 | GP: 0.89 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91795/150000 [1:15:35<18:48:43,  1.16s/it]G: 0.62 | D: 0.99 | GP: 0.12 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91842/150000 [1:16:32<19:24:30,  1.20s/it]G: 0.05 | D: 1.03 | GP: 0.10 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91898/150000 [1:17:38<19:14:02,  1.19s/it]G: 0.47 | D: 0.98 | GP: 0.54 | PL: 0.99\n",
            "foods<images3/foods>:  61% 91943/150000 [1:18:32<19:19:40,  1.20s/it]G: 1.09 | D: 0.87 | GP: 0.68 | PL: 0.98\n",
            "foods<images3/foods>:  61% 91999/150000 [1:19:38<18:40:17,  1.16s/it]G: 0.98 | D: 0.94 | GP: 0.48 | PL: 0.99\n",
            "foods<images3/foods>:  61% 92044/150000 [1:20:34<19:21:04,  1.20s/it]G: 1.07 | D: 0.78 | GP: 0.11 | PL: 0.99\n",
            "foods<images3/foods>:  61% 92093/150000 [1:21:33<19:29:56,  1.21s/it]G: 1.43 | D: 1.18 | GP: 0.12 | PL: 0.99\n",
            "foods<images3/foods>:  61% 92148/150000 [1:22:38<18:27:38,  1.15s/it]G: 0.58 | D: 1.04 | GP: 1.22 | PL: 0.99\n",
            "foods<images3/foods>:  61% 92193/150000 [1:23:33<19:42:52,  1.23s/it]G: 0.80 | D: 1.10 | GP: 0.07 | PL: 0.99\n",
            "foods<images3/foods>:  61% 92241/150000 [1:24:30<19:15:22,  1.20s/it]G: 1.09 | D: 0.92 | GP: 0.57 | PL: 0.99\n",
            "foods<images3/foods>:  62% 92299/150000 [1:25:38<18:55:14,  1.18s/it]G: 1.63 | D: 1.47 | GP: 0.53 | PL: 1.00\n",
            "foods<images3/foods>:  62% 92349/150000 [1:26:38<19:04:27,  1.19s/it]G: 1.35 | D: 0.72 | GP: 0.40 | PL: 1.00\n",
            "foods<images3/foods>:  62% 92395/150000 [1:27:32<18:54:11,  1.18s/it]G: -0.04 | D: 0.60 | GP: 0.05 | PL: 0.99\n",
            "foods<images3/foods>:  62% 92445/150000 [1:28:32<19:06:49,  1.20s/it]G: -0.00 | D: 0.98 | GP: 3.59 | PL: 0.99\n",
            "foods<images3/foods>:  62% 92492/150000 [1:29:27<18:40:38,  1.17s/it]G: 0.41 | D: 0.90 | GP: 0.43 | PL: 1.00\n",
            "foods<images3/foods>:  62% 92550/150000 [1:30:37<19:29:43,  1.22s/it]G: 1.23 | D: 0.76 | GP: 0.15 | PL: 0.99\n",
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          ],
          "name": "stdout"
        }
      ]
    }
  ]
}